Strategic Allocation

Based on Modern Portfolio Theory (MPT) and inferences from historical asset class returns, what are the best portfolio allocations for different levels of risk? In their February 2009 paper entitled “Strategic Asset Allocation: Determining the Optimal Portfolio with Ten Asset Classes”, Niels Bekkers, Ronald Doeswijk and Trevin Lam explore which asset classes add mean-variance diversification value to a traditional portfolio of stocks, bonds and cash and determine the weights of asset classes in optimal portfolios (maximum Sharpe ratio). Their total set of ten asset classes consists of stocks, government bonds, cash, private equity, real estate, hedge funds, commodities, high yield bonds, credits and inflation-linked bonds. Using mostly U.S. data as available for historical asset class returns and volatilities, they conclude that: Keep Reading

Is a “Rip Van Winkle” asset allocation strategy, wherein an investor gradually migrates from stocks to fixed income in pre-specified steps, optimum? Or, is there some simple, less passive alternative that takes equity bull and bear markets into account? In their November 2008 paper entitled “Dynamic Lifecycle Strategies for Target Date Retirement Funds”, Anup Basu, Alistair Byrne and Michael Drew question the rationale for pre-determined lifecycle equity/fixed income rebalancing and compare it to an alternative 40-year dynamic lifecycle strategy that flexibly rebalances depending on success to date. The dynamic strategy holds 100% stocks for the first 20 or 30 years and then annually switches partially to fixed income or remains 100% in stocks depending on whether or not it is achieving a target 10% annualized rate of return. The authors include 100% stocks and static balanced 60/30/10 stocks/bonds/cash strategies as benchmarks. Using bootstrapping to augment a dataset of annual nominal returns for U.S. stocks, bonds and bills spanning 1900-2004 (105 years), they conclude that: Keep Reading

Does increasingly powerful and more automated trading technology create the need for more sophisticated equity return benchmarks? In the December 2007 version of their paper entitled “130/30: The New Long-Only”, Andrew Lo and Pankaj Patel present a passive but dynamic “plain-vanilla” 130% long/30% short (130/30) benchmark index based on: (1) simple factors (encompassing value, growth, profitability, momentum and technical) to rank stocks; and, (2) standard methods for constructing a portfolio based on these rankings. Applying a standard portfolio optimizer to 10 well-known and commercially available valuation factors for S&P 500 stocks, with monthly rebalancing during 1/96-9/07, they find that: Keep Reading

With increasing business globalization and financial markets integration, can equity investors still get good risk reduction by diversifying their portfolios across country markets? Or, have other kinds of diversification become more important? In their paper entitled “The Changing Roles of Industry and Country Effects in the Global Equity Markets”, Kate Phylaktis and Lichuan Xia examine the evolution of country and industry effects on stock returns and diversification. Using weekly returns from the Dow Jones Global Indexes (DJGI) encompassing 4,801 companies in 51 industry groups across 34 countries over the period 1992 to 2001, they find that: Keep Reading

How many stocks are enough for the long-term investor to diversify stock-picking risks? Conventional wisdom says that 8 to 20 stocks are enough. In their recent paper entitled “Diversification in Portfolios of Individual Stocks: 100 Stocks Are Not Enough”, Dale Domian, David Louton and Marie Racine examine the risk that long-term buy-and-hold stock portfolios will fall short of some minimum return goal. They use portfolios of different sizes constructed from a real sample of 1,000 U.S. stocks (the 100 largest by market capitalization in each of 10 industries) over the 20-year period from January 1985 through December 2004, inserting comparable replacements for the hundreds of delistings that occur in the sample (mostly due to mergers). They find that: Keep Reading